Following unprecedented success on the natural language tasks, Transformers have been
successfully applied to several computer vision problems, achieving state-of-the-art results …

Supervised learning aims to build a function or model that seeks as many mappings as
possible between the training data and outputs, where each training data will predict as a …

The recent development in the areas of deep learning and deep convolutional neural
networks has significantly progressed and advanced the field of computer vision (CV) and …

Medical image analysis has two important research areas: disease grading and fine-grained
lesion segmentation. Although the former problem often relies on the latter, the two are …

Importance. With the booming growth of artificial intelligence (AI), especially the recent
advancements of deep learning, utilizing advanced deep learning-based methods for …

In modern‐day medicine, medical imaging has undergone immense advancements and can
capture several biomedical images from patients. In the wake of this, to assist medical …

Shortly after deep learning algorithms were applied to Image Analysis, and more importantly
to medical imaging, their applications increased significantly to become a trend. Likewise …

Background and objective Gastric cancer is the fifth most common cancer globally, and early
detection of gastric cancer is essential to save lives. Histopathological examination of gastric …

Medical-image-based diagnosis is a tedious task ‚and small lesions in various medical
images can be overlooked by medical experts due to the limited attention span of the human …

Breast cancer diagnosis based on medical imaging necessitates both fine-grained lesion
segmentation and disease grading. Although deep learning (DL) offers an emerging and …